The dataset I choose is NY NOAA(dataset_noaa.html). These data were accessed from the NOAA National Climatic Data Center.
stations %>%
filter(state == "NY") |>
mutate(text_label=str_c("Elevation:", elevation)) |>
filter(0<elevation & elevation<500) |>
plot_ly(x=~latitude,y=~longitude,color=~elevation,text=~text_label,
type="scatter", mode="markers",alpha=.2,colors="viridis") |>
layout(
title = "Scatter Plot of Station Elevations in NY",
xaxis = list(title = "Latitude"),
yaxis = list(title = "Longitude")
)
In this Scatter plot, I only included data in NY state that contains elevation between zero and 500.
stations %>%
count(element) |>
filter(n<100) |>
mutate(element= fct_reorder(element, n)) |>
plot_ly(x=~element,y=~n,color=~element,type="bar",colors="viridis") |>
layout(
title = "The count of Elements with Less than 100 Occurrences",
xaxis = list(title = "Element"),
yaxis = list(title = "Count")
)
In this bar plot, I only included counts of the variable elements less than 100.
stations |>
mutate(element=fct_reorder(element,elevation)) |>
filter(element %in% c("TMAX","TMIN","WT03","SNOW","SNWD")) |>
plot_ly(y=~elevation,color=~element,type="box",colors="viridis") |>
layout(
title = "Boxplot of Elevation by Weather Elements",
xaxis = list(title = "Weather Element"),
yaxis = list(title = "Elevation")
)
In this box plot, I only included data that have element in “TMAX”,“TMIN”,“WT03”,“SNOW”,“SNWD”.